Big Data Drive Deployment in a Connected Vehicle Environment
James Sayer, Director and Research Scientist – The University of Michigan Transportation Research Institute
Yiheng Feng, Assistant Research Scientist – The University of Michigan Transportation Research Institute
The data management and analytic requirements associated with collecting and interpreting connected vehicle data at scale are wide-ranging. Big Data Drive is a test and learn analytics methodology focused on connectivity, and it exists to accelerate internal capabilities to rapidly iterate, prototype, develop, and scale connectivity solutions for Ford Motor Company. Ultimately, Big Data Drive’s goal is to leap-frog present capabilities to compete in the future connected economy. At present, Big Data Drive collects data from Ford employees; the sample of vehicles and the vehicle operation patterns reflected in the collected data to date are not reflective of the wider vehicle population. Installing BDD devices in a captive fleet within the city of Ann Arbor will allow Ford to gain learnings from a more heterogeneous vehicle sample in an urban setting. In addition, expansion of existing BDD operations in Ann Arbor will facilitate a stronger understanding of how Ford will need to collect and process vehicle data in a connected environment. This final report from this project will not be publicly available.
Institution(s): University of Michigan Transportation Research Institute
Award Year: 2018
Research Thrust(s): Enabling Technology
Project Information Form